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6 April 1995 Statistical best bases for fast encoding in magnetic resonance imaging
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Abstract
We discuss the advantages and disadvantages of using a Karhunen-Loeve (K-L) expansion of a training set of images to reduce the number of encodes required for a magnetic resonance (MR) image of a new object. One form of this technique has been proposed and another implemented. We evaluate the error likely to be achieved as a function of the number of encodes and two technical problems: reduced SNR in the images and smoothing of the K-L functions in practice. As an alternative, we propose the use of joint best bases derived from the local trigonometric library as an approximation to the K-L basis. These bases approach the rate-distortion characteristic achieved by the K-L basis, but they are easier to use in MRI and can be applied with existing methods for fast acquisition.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dennis M. Healy, Douglas W. Warner, and John B. Weaver "Statistical best bases for fast encoding in magnetic resonance imaging", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205440; https://doi.org/10.1117/12.205440
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